PhD-position in structure-based ligand design using artificial intelligence based methods
Deadline: 06.01.2025
Publisert
The University of Bergen is a renowned educational and research institution, organised into seven faculties and approximately 54 institutes and academic centres. Campus is located in the centre of Bergen with university areas at Nygårdshøyden, Haukeland, Marineholmen, Møllendalsveien and Årstad.
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PhD position
At the Faculty of Medicine, Department of Biomedicine, in the group of Professor Ruth Brenk, a full-time PhD position is available for a period of three (3) years, or up to four months after the completion of the PhD degree, if this is achieved in less than three years. This position is funded by the EU Horizon Marie Skłodowska-Curie Action (MSCA) doctoral training network.
About the project/work tasks:
Drug discovery can be described as the hunt for small molecules that interact with a specific target to lead to a biological effect. The chemical space in which these small molecules can be found is tremendously large (up to 1060 molecules). Testing any significant fraction is impossible. Thus, automated De novo design methods are the long-standing Holy Grail of drug discovery. Unfortunately, these methods have so far failed to deliver. However, with new artificial intelligence (AI) methods new opportunities arise to get closer to this Holy Grail.
Currently, large research efforts are ongoing to develop AI methods suitable for De novo design and scoring functions to predict the affinities of the designed compounds. In fact, the field is so attractive that new methods are almost published weekly. However, the validation of the AI methods is often very limited. Mostly, no activity data for AI-generated or -scored compounds is presented. If such data is included, it is typically limited to protein kinases which are considered to be easy targets due to wealth of published data. The lack of validation using real-life drug discovery examples is seriously hampering the uptake of the methods in the field. Therefore, in this project we will work on validation of AI-based De novo design and scoring methods using both retrospective and prospective predictions.
The main objectives for the advertised PhD position are:
To compile a benchmark set for retro- and prospective predictions of AI-based scoring functions and De novo design methods
To carry out retrospective predictions of a range of AI-based scoring functions and De novo design methods
To carry out prospective predictions by designing ligands for targets for antibiotics (FabF) and cancer (NMT) and testing the designed ligands using binding assays and by determining the crystal structures of target-ligand complexes
Qualifications and personal qualities:
The applicant must hold a master`s degree or equivalent within the field of cheminformatics, bioinformatics, pharmacy, medicinal chemistry, or a related discipline.
Research experience in structure-based drug design is required.
Training in medicinal chemistry is required.
Training in high-performance chromatography is required.
The applicant must have a thorough understanding of the physico-chemical properties of small molecules and structure-based ligand design.
Basic knowledge of a scripting language is required.
Experience with RDKit is a distinct advantage.
The candidate must demonstrate a strong commitment and enthusiasm for structure-based drug design and the use of AI-based methods in this field.
The candidate must be able to work independently and interactively in a team setting.
A structured approach to work and excellent communication skills and fluency in both written and spoken English are required
The applicant’s personal suitability for the position is a significant factor in the evaluation.
About the PhD position:
The PhD-position:
PhD-positions are fixed term positions. You cannot be employed in a PhD-position for more than one fixed term period at the same institution or have had similar employment at an institution in the region.
Organized research training (PhD program):
The candidate must take part in the University of Bergen approved PhD programme leading to the degree within a time limit of 3 years. You must have admission to the organized research training (PhD program) at the Faculty in order to qualify for the position.
Application for admission to the PhD programme, including a project plan outline for the training plan must be submitted no later than three months after the date of commencement.
Your application must include:
A brief account of the applicant`s research interests and motivation for applying for the position
Certified copies of diplomas and transcripts of grades. Applicant whose education is from another country than Norway, need to also attach a certified translation of the diploma and transcript of grades to English or a Scandinavian language, if the original is not in any of these languages. It is also required that the applicant enclose a review from HK-dir (both bachelor and master degree) whether the education in question is of a scope and level that corresponds to the level of a Norwegian master’s degree. Please see https://hkdir.no/en/ for more information about HK-dir’s general recognition. This may take some time and we recommend you to apply as soon as you know you will apply for this position. If no answer within the application deadline, please enclose documentation from HK-dir that they have received your application
Complete list of publications and scientific work you want to be evaluated
Any publication in your name
Two references (name and contact information)
Applicant whose education is from another country than Norway, need to also attach a certified translation of the diploma and transcript of grades to English or a Scandinavian language, if the original is not in any of these languages. It is also required that the applicant enclose a review from the Norwegian Directorate for Higher Education and Skills (HK-dir) whether the education (bachelor and master degree) in question is of a scope and level that corresponds to the level of a Norwegian master’s degree. Please see https://hkdir.no/en/ for more information about HK-dir’s general recognition. The review from HK-dir may take some time and the application should be sent to HK-dir as soon as you have decided to apply for the position. If no answer within the application deadline, you must enclose documentation from HK-dir that they have received your application. Please note that the automatic recognition offered by HK-dir is not sufficient, and will not be accepted as basis for admission to the PhD programme. Applicants with education from a Nordic country or medical degree from the EEA area and a license to practice medicine in Norway are exempt from the requirement for HK-dir assessment, see Admission requirements at the Faculty of Medicine | Faculty of Medicine | UiB
See documentation requirements for language qualifications here.
We can offer:
Exciting development opportunities as part of your role in a strong professional environment
Salary NOK 540 500 (code 1017) in the state salary scale. For applicants with at least one year of employment in a position as a General Practitioner or Dentist, salary NOK 557 100 (code 1017). Medical specialist starts on salary NOK 575 400 (code 1017)
Enrolment in the Norwegian Public Service Pension Fund
University of Bergen must follow Norway’s export control regulations when processing applications for this position.
Diversity is a strength that enables us to solve our tasks even better. UiB therefore needs qualified employees regardless of gender, ethnicity, religion, worldview, disability, sexual orientation, gender identity, gender expression, and age.
The University of Bergen applies the principle of public access to information when recruiting staff for academic positions.
Information about applicants may be made public even if the applicant has asked not to be named on the list of persons who have applied. The applicant must be notified if the request to be omitted is not met.
The successful applicant must comply with the guidelines that apply to the position at all times.
We encourage applicants with disabilities, immigrant backgrounds, or gaps in their CV to apply. By indicating such circumstances in your application, you may receive favourable consideration. We ensure that at least one qualified applicant from each of these groups is invited for an interview as part of our commitment to inclusivity and equal opportunity. For further information about the recruitment process, click here.
